Data-driven scenario analysis supports the revival of historic silvoarable systems for carbon smart rural landscapes

数据驱动的情景分析支持恢复历史悠久的林农系统,以打造碳智能型农村景观。

阅读:1

Abstract

Agroforestry has long been recognised as a nature-based solution for climate mitigation, yet its adoption in Europe has drastically declined due to the socio-economic transformations and land use intensification since the onset of the Great Acceleration (ca. mid-twentieth century). This study reconstructs the historical role of agroforestry in Northern Italy by drawing on century-long land use records (1929-2024) and historical sources, which were crucial for identifying and modelling the carbon stock of traditional silvoarable systems. Through the integration of Monte Carlo simulations and scenario-based modelling, we estimate that historic silvoarable systems stored an average of 75.4 t C ha(-1), with a potential range of 50.4-101.6 t C ha(-1). The widespread abandonment of agroforestry practices led to a 97% reduction in their extent, accompanied by a corresponding expansion of monocultures. Future management scenarios suggest that restoring silvoarable systems could enhance regional carbon sequestration by up to 12%, a gain comparable to afforestation strategies requiring the conversion of 25% of existing farmland. Our findings underscore the global value of traditional ecological knowledge and historical land use strategies in informing carbon-smart agricultural transitions and shaping policies for resilient, multifunctional landscapes.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。